An open-access database and analysis tool for perovskite solar cells based on the FAIR data principles

Large datasets are now ubiquitous as technology enables higher-throughput experiments, but rarely can a research field truly benefit from the research data generated due to inconsistent formatting, undocumented storage or improper dissemination. Here we extract all the meaningful device data from peer-reviewed papers on metal-halide perovskite solar cells published so far and make them available in a database. We collect data from over 42,400 photovoltaic devices with up to 100 parameters per device. We then develop open-source and accessible procedures to analyse the data, providing examples of insights that can be gleaned from the analysis of a large dataset. The database, graphics and analysis tools are made available to the community and will continue to evolve as an open-source initiative. This approach of extensively capturing the progress of an entire field, including sorting, interactive exploration and graphical representation of the data, will be applicable to many fields in materials science, engineering and biosciences

An open-access database and analysis tool for perovskite solar cells based on the FAIR data principles

Large datasets are now ubiquitous as technology enables higher-throughput experiments, but rarely can a research field truly benefit from the research data generated due to inconsistent formatting, undocumented storage or improper dissemination. Here we extract all the meaningful device data from peer-reviewed papers on metal-halide perovskite solar cells published so far and make them available in a database. We collect data from over 42, 400 photovoltaic devices with up to 100 parameters per device. We then develop open-source and accessible procedures to analyse the data, providing examples of insights that can be gleaned from the analysis of a large dataset. The database, graphics and analysis tools are made available to the community and will continue to evolve as an open-source initiative. This approach of extensively capturing the progress of an entire field, including sorting, interactive exploration and graphical representation of the data, will be applicable to many fields in materials science, engineering and biosciences. © 2021, The Author(s)

An open-access database and analysis tool for perovskite solar cells based on the FAIR data principles

AbstractLarge datasets are now ubiquitous as technology enables higher-throughput experiments, but rarely can a research field truly benefit from the research data generated due to inconsistent formatting, undocumented storage or improper dissemination. Here we extract all the meaningful device data from peer-reviewed papers on metal-halide perovskite solar cells published so far and make them available in a database. We collect data from over 42,400 photovoltaic devices with up to 100 parameters per device. We then develop open-source and accessible procedures to analyse the data, providing examples of insights that can be gleaned from the analysis of a large dataset. The database, graphics and analysis tools are made available to the community and will continue to evolve as an open-source initiative. This approach of extensively capturing the progress of an entire field, including sorting, interactive exploration and graphical representation of the data, will be applicable to many fields in materials science, engineering and biosciences.</jats:p

Klasteryzacja k-średnich obrazów teksturowych lamelarnych mikrostruktur stopów tytanu

This paper presents an implementation of the k-means clustering method, to segment cross sections of X-ray micro tomographic images of lamellar Titanium alloys. It proposes an approach for estimating the optimal number of clusters by analyzing the histogram of the local orientation map of the image and the choice of the cluster centroids used to initialize k-means. This is compared with the classical method considering random coordinates of the clusters.W artykule przedstawiono implementację metody klasteryzacji k-średnich, do segmentacji dwuwymiarowych rentgenowskich obrazów mikro tomograficznych lamelarnych stopów tytanu. Zaproponowano metody szacowania optymalnej liczbę klastrów oraz wyboru centro idów poprzez analizę histogramu mapy lokalnych kierunków obrazu. Dokonano porównania zaproponowanych metod z losowym doborem początkowego położenia klastrów

ZnO Nanopowders as Chemical Sensor to Malathion Vapor

Thick films of zinc oxide (ZnO) nanopowders have been prepared by high energy ball-milling for various spans of mill time (3-18 h). The morphology and crystal structure of the prepared ZnO powder were characterized by scanning electron microscope and X-ray diffraction. The ZnO thick films were then used to construct a gas sensor for O,O-dimethyl dithiophosphate of diethyl mercaptosuccinate (malathion) at different operating temperatures. The sensor response at 100 ppm of malathion was found to reach a maximum as large as 80 at 6 h of high energy ball-milling, four times larger than that found for ethanol. Scanning electron microscope observation of the granular state and pore size distribution analyses indicated that increasing high energy ball-milling time gave rise especially to an increase in the volume of pores in the pore size range of 6-35 nm. It is suggested that such a change in nanostructure is responsible for the marked promotion of the response to malathion

The Ontological (In)security of Similarity: Wahhabism versus Islamism in Saudi Foreign Policy

It has long been argued that identity matters in international relations. Yet, how identity impacts enmity and conflict among states remains the subject of debate. The existing literature asserts that differences in identity can be a source of conflict, whereas convergence and similarity lead to cooperation. Nevertheless, empirical evidence from the Middle East has long defied this hypothesis. The Kingdom of Saudi Arabia, which prides itself on being an Islamic model and claims Islamic leadership, has opposed the rise to power of Islamist movements in the Middle East. To address this paradox, this article builds on the growing literature on ontological security to propose a theoretical framework explaining how similarity can generate anxiety and identity risks. This framework, I argue, moves beyond traditional regime‐security approaches to reveal that security is not only physical but also ontological. I then illustrate the argument through a comparison of Saudi identity risks in the wake of the Iranian revolution (1979) and the ascendance of the Muslim Brotherhood to power in Egypt (2012). Ultimately, these cases provide intriguing insights into foreign policy behaviour during critical situations